root/modules/calib3d/test/test_solvepnp_ransac.cpp

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DEFINITIONS

This source file includes following definitions.
  1. generate3DPointCloud
  2. generateCameraMatrix
  3. generateDistCoeffs
  4. generatePose
  5. runTest
  6. run
  7. runTest
  8. TEST
  9. TEST
  10. TEST
  11. TEST
  12. TEST

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#include "test_precomp.hpp"

#ifdef HAVE_TBB
#include "tbb/task_scheduler_init.h"
#endif

using namespace cv;
using namespace std;

class CV_solvePnPRansac_Test : public cvtest::BaseTest
{
public:
    CV_solvePnPRansac_Test()
    {
        eps[SOLVEPNP_ITERATIVE] = 1.0e-2;
        eps[SOLVEPNP_EPNP] = 1.0e-2;
        eps[SOLVEPNP_P3P] = 1.0e-2;
        eps[SOLVEPNP_DLS] = 1.0e-2;
        eps[SOLVEPNP_UPNP] = 1.0e-2;
        totalTestsCount = 10;
    }
    ~CV_solvePnPRansac_Test() {}
protected:
    void generate3DPointCloud(vector<Point3f>& points, Point3f pmin = Point3f(-1,
        -1, 5), Point3f pmax = Point3f(1, 1, 10))
    {
        const Point3f delta = pmax - pmin;
        for (size_t i = 0; i < points.size(); i++)
        {
            Point3f p(float(rand()) / RAND_MAX, float(rand()) / RAND_MAX,
                float(rand()) / RAND_MAX);
            p.x *= delta.x;
            p.y *= delta.y;
            p.z *= delta.z;
            p = p + pmin;
            points[i] = p;
        }
    }

    void generateCameraMatrix(Mat& cameraMatrix, RNG& rng)
    {
        const double fcMinVal = 1e-3;
        const double fcMaxVal = 100;
        cameraMatrix.create(3, 3, CV_64FC1);
        cameraMatrix.setTo(Scalar(0));
        cameraMatrix.at<double>(0,0) = rng.uniform(fcMinVal, fcMaxVal);
        cameraMatrix.at<double>(1,1) = rng.uniform(fcMinVal, fcMaxVal);
        cameraMatrix.at<double>(0,2) = rng.uniform(fcMinVal, fcMaxVal);
        cameraMatrix.at<double>(1,2) = rng.uniform(fcMinVal, fcMaxVal);
        cameraMatrix.at<double>(2,2) = 1;
    }

    void generateDistCoeffs(Mat& distCoeffs, RNG& rng)
    {
        distCoeffs = Mat::zeros(4, 1, CV_64FC1);
        for (int i = 0; i < 3; i++)
            distCoeffs.at<double>(i,0) = rng.uniform(0.0, 1.0e-6);
    }

    void generatePose(Mat& rvec, Mat& tvec, RNG& rng)
    {
        const double minVal = 1.0e-3;
        const double maxVal = 1.0;
        rvec.create(3, 1, CV_64FC1);
        tvec.create(3, 1, CV_64FC1);
        for (int i = 0; i < 3; i++)
        {
            rvec.at<double>(i,0) = rng.uniform(minVal, maxVal);
            tvec.at<double>(i,0) = rng.uniform(minVal, maxVal/10);
        }
    }

    virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* epsilon, double& maxError)
    {
        Mat rvec, tvec;
        vector<int> inliers;
        Mat trueRvec, trueTvec;
        Mat intrinsics, distCoeffs;
        generateCameraMatrix(intrinsics, rng);
        if (method == 4) intrinsics.at<double>(1,1) = intrinsics.at<double>(0,0);
        if (mode == 0)
            distCoeffs = Mat::zeros(4, 1, CV_64FC1);
        else
            generateDistCoeffs(distCoeffs, rng);
        generatePose(trueRvec, trueTvec, rng);

        vector<Point2f> projectedPoints;
        projectedPoints.resize(points.size());
        projectPoints(Mat(points), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints);
        for (size_t i = 0; i < projectedPoints.size(); i++)
        {
            if (i % 20 == 0)
            {
                projectedPoints[i] = projectedPoints[rng.uniform(0,(int)points.size()-1)];
            }
        }

        solvePnPRansac(points, projectedPoints, intrinsics, distCoeffs, rvec, tvec,
            false, 500, 0.5f, 0.99, inliers, method);

        bool isTestSuccess = inliers.size() >= points.size()*0.95;

        double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec);
        isTestSuccess = isTestSuccess && rvecDiff < epsilon[method] && tvecDiff < epsilon[method];
        double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff;
        //cout << error << " " << inliers.size() << " " << eps[method] << endl;
        if (error > maxError)
            maxError = error;

        return isTestSuccess;
    }

    void run(int)
    {
        ts->set_failed_test_info(cvtest::TS::OK);

        vector<Point3f> points, points_dls;
        const int pointsCount = 500;
        points.resize(pointsCount);
        generate3DPointCloud(points);

        const int methodsCount = 5;
        RNG rng = ts->get_rng();


        for (int mode = 0; mode < 2; mode++)
        {
            for (int method = 0; method < methodsCount; method++)
            {
                double maxError = 0;
                int successfulTestsCount = 0;
                for (int testIndex = 0; testIndex < totalTestsCount; testIndex++)
                {
                    if (runTest(rng, mode, method, points, eps, maxError))
                        successfulTestsCount++;
                }
                //cout <<  maxError << " " << successfulTestsCount << endl;
                if (successfulTestsCount < 0.7*totalTestsCount)
                {
                    ts->printf( cvtest::TS::LOG, "Invalid accuracy for method %d, failed %d tests from %d, maximum error equals %f, distortion mode equals %d\n",
                        method, totalTestsCount - successfulTestsCount, totalTestsCount, maxError, mode);
                    ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
                }
                cout << "mode: " << mode << ", method: " << method << " -> "
                     << ((double)successfulTestsCount / totalTestsCount) * 100 << "%"
                     << " (err < " << maxError << ")" << endl;
            }
        }
    }
    double eps[5];
    int totalTestsCount;
};

class CV_solvePnP_Test : public CV_solvePnPRansac_Test
{
public:
    CV_solvePnP_Test()
    {
        eps[SOLVEPNP_ITERATIVE] = 1.0e-6;
        eps[SOLVEPNP_EPNP] = 1.0e-6;
        eps[SOLVEPNP_P3P] = 1.0e-4;
        eps[SOLVEPNP_DLS] = 1.0e-4;
        eps[SOLVEPNP_UPNP] = 1.0e-4;
        totalTestsCount = 1000;
    }

    ~CV_solvePnP_Test() {}
protected:
    virtual bool runTest(RNG& rng, int mode, int method, const vector<Point3f>& points, const double* epsilon, double& maxError)
    {
        Mat rvec, tvec;
        Mat trueRvec, trueTvec;
        Mat intrinsics, distCoeffs;
        generateCameraMatrix(intrinsics, rng);
        if (method == 4) intrinsics.at<double>(1,1) = intrinsics.at<double>(0,0);
        if (mode == 0)
            distCoeffs = Mat::zeros(4, 1, CV_64FC1);
        else
            generateDistCoeffs(distCoeffs, rng);
        generatePose(trueRvec, trueTvec, rng);

        std::vector<Point3f> opoints;
        if (method == 2)
        {
            opoints = std::vector<Point3f>(points.begin(), points.begin()+4);
        }
        else if(method == 3)
        {
            opoints = std::vector<Point3f>(points.begin(), points.begin()+50);
        }
        else
            opoints = points;

        vector<Point2f> projectedPoints;
        projectedPoints.resize(opoints.size());
        projectPoints(Mat(opoints), trueRvec, trueTvec, intrinsics, distCoeffs, projectedPoints);

        solvePnP(opoints, projectedPoints, intrinsics, distCoeffs, rvec, tvec,
            false, method);

        double rvecDiff = norm(rvec-trueRvec), tvecDiff = norm(tvec-trueTvec);
        bool isTestSuccess = rvecDiff < epsilon[method] && tvecDiff < epsilon[method];

        double error = rvecDiff > tvecDiff ? rvecDiff : tvecDiff;
        if (error > maxError)
            maxError = error;

        return isTestSuccess;
    }
};

TEST(Calib3d_SolvePnPRansac, accuracy) { CV_solvePnPRansac_Test test; test.safe_run(); }
TEST(Calib3d_SolvePnP, accuracy) { CV_solvePnP_Test test; test.safe_run(); }

TEST(Calib3d_SolvePnPRansac, concurrency)
{
    int count = 7*13;

    Mat object(1, count, CV_32FC3);
    randu(object, -100, 100);

    Mat camera_mat(3, 3, CV_32FC1);
    randu(camera_mat, 0.5, 1);
    camera_mat.at<float>(0, 1) = 0.f;
    camera_mat.at<float>(1, 0) = 0.f;
    camera_mat.at<float>(2, 0) = 0.f;
    camera_mat.at<float>(2, 1) = 0.f;

    Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));

    vector<cv::Point2f> image_vec;
    Mat rvec_gold(1, 3, CV_32FC1);
    randu(rvec_gold, 0, 1);
    Mat tvec_gold(1, 3, CV_32FC1);
    randu(tvec_gold, 0, 1);
    projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);

    Mat image(1, count, CV_32FC2, &image_vec[0]);

    Mat rvec1, rvec2;
    Mat tvec1, tvec2;

    {
        // limit concurrency to get deterministic result
        theRNG().state = 20121010;
        setNumThreads(1);
        solvePnPRansac(object, image, camera_mat, dist_coef, rvec1, tvec1);
    }

    {
        Mat rvec;
        Mat tvec;
        // parallel executions
        for(int i = 0; i < 10; ++i)
        {
            cv::theRNG().state = 20121010;
            solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
        }
    }

    {
        // single thread again
        theRNG().state = 20121010;
        setNumThreads(1);
        solvePnPRansac(object, image, camera_mat, dist_coef, rvec2, tvec2);
    }

    double rnorm = cvtest::norm(rvec1, rvec2, NORM_INF);
    double tnorm = cvtest::norm(tvec1, tvec2, NORM_INF);

    EXPECT_LT(rnorm, 1e-6);
    EXPECT_LT(tnorm, 1e-6);
}

TEST(Calib3d_SolvePnP, double_support)
{
    Matx33d intrinsics(5.4794130238156129e+002, 0., 2.9835545700043139e+002, 0.,
                       5.4817724002728005e+002, 2.3062194051986233e+002, 0., 0., 1.);
    std::vector<cv::Point3d> points3d;
    std::vector<cv::Point2d> points2d;
    std::vector<cv::Point3f> points3dF;
    std::vector<cv::Point2f> points2dF;
    for (int i = 0; i < 10 ; i++)
    {
        points3d.push_back(cv::Point3d(i,0,0));
        points3dF.push_back(cv::Point3d(i,0,0));
        points2d.push_back(cv::Point2d(i,0));
        points2dF.push_back(cv::Point2d(i,0));
    }
    Mat R,t, RF, tF;
    vector<int> inliers;

    solvePnPRansac(points3dF, points2dF, intrinsics, cv::Mat(), RF, tF, true, 100, 8.f, 0.999, inliers, cv::SOLVEPNP_P3P);
    solvePnPRansac(points3d, points2d, intrinsics, cv::Mat(), R, t, true, 100, 8.f, 0.999, inliers, cv::SOLVEPNP_P3P);

    ASSERT_LE(norm(R, Mat_<double>(RF), NORM_INF), 1e-3);
    ASSERT_LE(norm(t, Mat_<double>(tF), NORM_INF), 1e-3);
}

TEST(Calib3d_SolvePnP, translation)
{
    Mat cameraIntrinsic = Mat::eye(3,3, CV_32FC1);
    vector<float> crvec;
    crvec.push_back(0.f);
    crvec.push_back(0.f);
    crvec.push_back(0.f);
    vector<float> ctvec;
    ctvec.push_back(100.f);
    ctvec.push_back(100.f);
    ctvec.push_back(0.f);
    vector<Point3f> p3d;
    p3d.push_back(Point3f(0,0,0));
    p3d.push_back(Point3f(0,0,10));
    p3d.push_back(Point3f(0,10,10));
    p3d.push_back(Point3f(10,10,10));
    p3d.push_back(Point3f(2,5,5));

    vector<Point2f> p2d;
    projectPoints(p3d, crvec, ctvec, cameraIntrinsic, noArray(), p2d);
    Mat rvec;
    Mat tvec;
    rvec =(Mat_<float>(3,1) << 0, 0, 0);
    tvec = (Mat_<float>(3,1) << 100, 100, 0);

    solvePnP(p3d, p2d, cameraIntrinsic, noArray(), rvec, tvec, true);
    ASSERT_TRUE(checkRange(rvec));
    ASSERT_TRUE(checkRange(tvec));

    rvec =(Mat_<double>(3,1) << 0, 0, 0);
    tvec = (Mat_<double>(3,1) << 100, 100, 0);
    solvePnP(p3d, p2d, cameraIntrinsic, noArray(), rvec, tvec, true);
    ASSERT_TRUE(checkRange(rvec));
    ASSERT_TRUE(checkRange(tvec));

    solvePnP(p3d, p2d, cameraIntrinsic, noArray(), rvec, tvec, false);
    ASSERT_TRUE(checkRange(rvec));
    ASSERT_TRUE(checkRange(tvec));
}

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